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Bayesian alignment of proteins via Delaunay tetrahedralization

Author

Listed:
  • S.M. Najibi
  • M.R. Faghihi
  • M. Golalizadeh
  • S.S. Arab

Abstract

An active area of research in bioinformatics is finding structural similarity of proteins by alignment. Among many methods, the popular one is to find the similarity based on statistical features. This method involves gathering information from the complex biomolecule structure and obtaining the best alignment by maximizing the number of matched features. In this paper, after reviewing statistical models for matching the structural biomolecule, it is shown that local alignment based on the Delaunay tetrahedralization (DT) can be used for Bayesian alignment of proteins. In this method, we use DT to add a priori structural information of protein in the Bayesian methodology. We demonstrate that this method shows advantages over competing methods in achieving a global alignment of proteins, accelerating the convergence rate and improving the parameter estimates.

Suggested Citation

  • S.M. Najibi & M.R. Faghihi & M. Golalizadeh & S.S. Arab, 2015. "Bayesian alignment of proteins via Delaunay tetrahedralization," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 1064-1079, May.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:5:p:1064-1079
    DOI: 10.1080/02664763.2014.995605
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    References listed on IDEAS

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    1. Peter J. Green & Kanti V. Mardia, 2006. "Bayesian alignment using hierarchical models, with applications in protein bioinformatics," Biometrika, Biometrika Trust, vol. 93(2), pages 235-254, June.
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    Cited by:

    1. Ejlali Nasim & Faghihi Mohammad Reza & Sadeghi Mehdi, 2017. "Bayesian comparison of protein structures using partial Procrustes distance," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(4), pages 243-257, September.

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